Master of Electrical Engineering (MEE) Degree
Program Learning Outcomes for the MEE Degree
Upon completing the MEE degree, students will be able to:
- Apply the principles of mathematics and science necessary to solve advanced electrical engineering problems.
- Practice at an advanced level in at least one of the major sub-fields of electrical engineering.
Requirements for the MEE Degree
The MEE degree is a non-thesis master's degree. For general university requirements, please see Non-Thesis Master's Degrees. For additional requirements, regulations, and procedures for all graduate programs, please see All Graduate Students. Students pursuing the MEE degree must complete:
- A minimum of 10 courses (30 credit hours) to satisfy degree requirements.
- A minimum of 30 credit hours of graduate-level study (coursework at the 500-level or above).
- A minimum of 27 credit hours must be taken at Rice University.
- A minimum residency enrollment of one fall or spring semester of part-time graduate study at Rice University.
- A minimum of 3 courses (9 credit hours) from the core requirements.
- The requirements for one area of specialization (see below for areas of specialization). The MEE degree program offers five areas of specialization, or focus areas:
- A minimum of 4 courses (12 credit hours) from the elective requirements:
- 2 courses (6 credit hours) from the General MEE requirement
- 2 courses (6 credit hours) from the Free Elective requirement.
- ELEC 698 each semester in residence at Rice University.
- A maximum of 1 course (3 credit hours) of graduate-level coursework as transfer credit. For additional departmental guidelines regarding transfer credit, see the Policies tab.
- A minimum overall GPA of 2.67.
- A minimum GPA of 3.00 in required coursework with a minimum grade of C (2.00 grade points) in each course.
Students are admitted to the MEE degree program in the fall semester. MEE students are to consult with an academic advisor on the MEE Committee each semester in order to identify and clearly document their individual curricular requirements or degree plan to be followed. An MEE degree planning form and current requirements may be found on the ECE website.
The courses listed below satisfy the requirements for this degree program. In certain instances, courses not on this official list may be substituted upon approval of the program's academic advisor, or where applicable, the department or program's Director of Graduate Studies. (Course substitutions must be formally applied and entered into Degree Works by the department or program's Official Certifier.) Students and their academic advisors should identify and clearly document the courses to be taken.
Summary
Code | Title | Credit Hours |
---|---|---|
Total Credit Hours Required for the MEE Degree | 30 |
Degree Requirements
Code | Title | Credit Hours |
---|---|---|
Core Requirements | ||
Select 3 from the following: | 9-11 | |
HIGH PERFORMANCE COMPUTER ARCHITECTURE | ||
INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS | ||
COMMUNICATION NETWORKS | ||
INTRODUCTION TO COMPUTER VISION | ||
MACHINE LEARNING AND SIGNAL PROCESSING FOR NEURO ENGINEERING | ||
DIGITAL COMMUNICATION | ||
MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION | ||
DIGITAL SIGNAL PROCESSING | ||
INTRODUCTION TO SOLID STATE PHYSICS I | ||
LASER SPECTROSCOPY | ||
LEARNING FROM SENSOR DATA | ||
FUNDAMENTALS OF HUMAN NEUROIMAGING | ||
Area of Specialization | ||
Select 1 of the following Areas of Specialization (see Areas of Specialization below): | 8-11 | |
Computer Engineering | ||
Data Science | ||
Neuroengineering | ||
Photonics, Electronics, and Nano-devices | ||
Systems | ||
Elective Requirements | ||
General MEE Requirement: select 2 additional courses from any of the courses that qualify as Core Requirement courses or that fulfill any of the Areas of Specialization | 6 | |
Free Elective Requirement: select 2 additional courses as free electives 1 | 6 | |
Professional Master's Seminar | ||
ELEC 698 | ECE PROFESSIONAL MASTERS SEMINAR SERIES (required each semester in-residence at Rice University, credit hours earned do not apply towards degree requirements) 2 | 1 |
Total Credit Hours | 30 |
Footnotes and Additional Information
1 | Free electives may be fulfilled by any 2 courses (6 credit hours) selected from the following:
|
2 | ELEC 698 is taken for a Satisfactory/Unsatisfactory grade and must be completed with a Satisfactory grade, however, this course does not apply to the requirement of a minimum grade of C (2.00 grade points) in each required course. |
Areas of Specialization
Students must complete a minimum of 3 courses (9 credit hours) from one Area of Specialization and may select up to 2 additional courses (6 credit hours) from any Area of Specialization (or from the Core Requirements) to fulfill Elective Requirements.
Area of Specialization: Computer Engineering
Code | Title | Credit Hours |
---|---|---|
Select 3 from the following: | 9-11 | |
COMPLEXITY IN MODERN SYSTEMS | ||
ADVANCED DIGITAL INTEGRATED CIRCUITS DESIGN | ||
ADVANCED VLSI DESIGN | ||
HIGH PERFORMANCE COMPUTER ARCHITECTURE | ||
VLSI SYSTEMS DESIGN | ||
MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION | ||
COMPUTER SYSTEMS ARCHITECTURE | ||
Total Credit Hours | 9-11 |
Area of Specialization: Data Science
Code | Title | Credit Hours |
---|---|---|
Select 3 from the following: | 9-10 | |
NEURAL MACHINE LEARNING I | ||
or COMP 540 | STATISTICAL MACHINE LEARNING | |
STATISTICAL SIGNAL PROCESSING | ||
INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS | ||
INFORMATION THEORY | ||
INTRODUCTION TO COMPUTER VISION | ||
DIGITAL SIGNAL PROCESSING | ||
LEARNING FROM SENSOR DATA | ||
A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING | ||
INTRODUCTION TO MACHINE LEARNING | ||
ADVANCED TOPICS IN SIGNAL PROCESSING AND MACHINE LEARNING | ||
Total Credit Hours | 9-10 |
Area of Specialization: Neuroengineering
Code | Title | Credit Hours |
---|---|---|
Select 3 from the following: | 9-10 | |
NEURAL MACHINE LEARNING I | ||
INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS | ||
MACHINE LEARNING AND SIGNAL PROCESSING FOR NEURO ENGINEERING | ||
FUNDAMENTALS OF HUMAN NEUROIMAGING | ||
FUNDAMENTALS OF MEDICAL IMAGING I | ||
THEORETICAL NEUROSCIENCE I: BIOPHYSICAL MODELING OF CELLS AND CIRCUITS | ||
NEURAL COMPUTATION | ||
NANO-NEUROTECHNOLOGY | ||
INTRODUCTION TO COMPUTATIONAL NEURSCIENCE | ||
Total Credit Hours | 9-10 |
Area of Specialization: Photonics, Electronics, and Nano-devices
Code | Title | Credit Hours |
---|---|---|
Select 3 from the following: | 8-9 | |
PHYSICS OF SENSOR MATERIALS AND NANOSENSOR TECHNOLOGY | ||
OPTOELECTRONIC DEVICES | ||
INTRODUCTION TO SOLID STATE PHYSICS I | ||
NANO-OPTICS | ||
LASER SPECTROSCOPY | ||
ULTRAFAST OPTICAL PHENOMENA | ||
IMAGING AT THE NANOSCALE | ||
TOPICS IN NANOPHOTONICS | ||
COMPUTATIONAL ELECTRODYNAMICS AND NANOPHOTONICS | ||
Total Credit Hours | 8-9 |
Area of Specialization: Systems
Code | Title | Credit Hours |
---|---|---|
Select 3 from the following: | 9 | |
STATISTICAL SIGNAL PROCESSING | ||
INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS | ||
INFORMATION THEORY | ||
COMMUNICATION NETWORKS | ||
INTRODUCTION TO COMMUNICATION NETWORKS | ||
THE APPLICATION OF VECTOR SPACE METHODS AND OTHER ADVANCED TECHNIQUES TO DSP | ||
INTRODUCTION TO COMPUTER VISION | ||
COMPUTER VISION | ||
COMPUTATIONAL PHOTOGRAPHY | ||
DIGITAL COMMUNICATION | ||
DIGITAL SIGNAL PROCESSING | ||
Total Credit Hours | 9 |
Policies for the MEE Degree
Department of Electrical and Computer Engineering Graduate Program Handbook
The General Announcements (GA) is the official Rice curriculum. As an additional resource for students, the department of Electrical and Computer Engineering publishes a graduate program handbook, which can be found here:
http://gradhandbooks.rice.edu/2018_19/Electrical_Computer_Engineering_MME_Handbook.pdf
Transfer Credit
For Rice University’s policy regarding transfer credit, see Transfer Credit. Some departments and programs have additional restrictions on transfer credit. Students are encouraged to meet with their academic program’s advisor when considering transfer credit possibilities.
Departmental Transfer Credit Guidelines
Students pursuing the MEE degree in the field of Electrical and Computer Engineering should be aware of the following departmental transfer credit guidelines:
- No more than 1 course (3 credit hours) of transfer credit from U.S. or international universities of similar standing as Rice may apply towards the degree.
- Requests for transfer credit will be considered by the program director (and/or the program’s official transfer credit advisor) on an individual case-by-case basis.
Additional Information
For additional information, please see the Electrical and Computer Engineering website: https://www.ece.rice.edu/
Opportunities for the MEE Degree
Fifth-Year Master's Degree Option for Rice Undergraduate Students
Rice students have an option to pursue the Master of Electrical Engineering (MEE) degree by adding an additional fifth year to their four undergraduate years of science and engineering studies.
Advanced Rice undergraduate students in good academic standing may apply to the MEE degree program during their junior or senior year. Upon acceptance, depending on course load, financial aid status, and other variables, they may then start taking some required courses of the master's degree program. A plan of study will need to be approved by the student's undergraduate advisor and the MEE program director.
As part of this option and opportunity, Rice undergraduate students:
- must complete the requirements for a bachelor's degree and the master's degree independently of each other (i.e. no course may be counted toward the fulfillment of both degrees).
- should be aware there could be financial aid implications if the conversion of undergraduate coursework to that of graduate level reduces their earned undergraduate credit for any semester below that of full-time status (12 credit hours).
- more information on this Undergraduate - Graduate Concurrent Enrollment opportunity, including specific information on the registration process can be found here.
Additional Information
For additional information, please see the Electrical and Computer Engineering website: https://www.ece.rice.edu/